Subjective andObjective Data Modelling — Learn free

Self-check

Questions 1–10 of 10

1. What is the answer given to the question 'Do we really need data modelling anymore?'
Question 1A. Modelling is obsolete in cloud-native platformsB. Modelling is only needed for OLTP systemsC. There is no such thing as data without a model; every stored structure is a data modelD. Modelling is only needed when using schema-on-readE. Modelling is optional once a data lake exists
2. Which type of system is Subjective Data Modelling commonly associated with?
Question 2A. Data warehouses and OLAP cubesB. Transactional OLTP systems using normalised structures such as 3NFC. Semantic layers for BID. Machine learning feature storesE. Data lakes with schema-on-read
3. What question does Objective Data Modelling start from?
Question 3A. How does the system store data?B. How can redundancy be eliminated?C. Which foreign keys enforce referential integrity?D. How does the business need to analyse the data?E. Which database vendor should be used?
4. In the retail analytics example of Objective Data Modelling, which of these is stored in the central fact table?
Question 4A. SalesAmount, Quantity and DiscountB. Customer names and addressesC. Product descriptionsD. Geographic region hierarchiesE. Calendar attributes such as month and quarter
5. Why is denormalisation deliberately introduced in Objective Data Modelling?
Question 5A. To enforce referential integrityB. To reduce storage costC. To simplify reporting and improve query performanceD. To speed up transaction insertsE. To satisfy Third Normal Form
6. Which phrase summarises what Subjective Data Modelling protects?
Question 6A. Business understandingB. Operational truthC. Analytical flexibilityD. Aggregation performanceE. Strategic decision-making
7. In which direction is Objective Data Modelling typically designed?
Question 7A. Bottom-up from the application codeB. Sideways from other departments' modelsC. Randomly, as data arrivesD. Top-down, guided by business questionsE. From the physical storage layer upwards
8. What happens to modelling in schema-on-read architectures if it is not done deliberately?
Question 8A. It disappears entirelyB. It is handled automatically by the storage formatC. It emerges accidentally through ad hoc transformations and inconsistent metric definitionsD. It is replaced by data governanceE. It becomes unnecessary because the data is flexible
9. Which of the following is NOT listed as a result of intentional modelling?
Question 9A. Definitions are clearB. KPIs are alignedC. Governance is manageableD. Trust in data increasesE. Reports disagree
10. What is described as the real sign of architectural maturity?
Question 10A. Whether data is modelled intentionallyB. Whether the organisation uses a star schemaC. Whether all data is in Third Normal FormD. Whether the platform is cloud-nativeE. Whether modelling has been eliminated